bool FootstepGraph::isGoal(StatePtr state)
{
FootstepState::Ptr goal = getGoal(state->getLeg());
if (publish_progress_) {
jsk_footstep_msgs::FootstepArray msg;
msg.header.frame_id = "odom"; // TODO fixed frame_id
msg.header.stamp = ros::Time::now();
msg.footsteps.push_back(*state->toROSMsg());
pub_progress_.publish(msg);
}
Eigen::Affine3f pose = state->getPose();
Eigen::Affine3f goal_pose = goal->getPose();
Eigen::Affine3f transformation = pose.inverse() * goal_pose;
if ((parameters_.goal_pos_thr > transformation.translation().norm()) &&
(parameters_.goal_rot_thr > std::abs(Eigen::AngleAxisf(transformation.rotation()).angle()))) {
// check collision
if (state->getLeg() == jsk_footstep_msgs::Footstep::LEFT) {
if (right_goal_state_->crossCheck(state)) {
return true;
}
} else if (state->getLeg() == jsk_footstep_msgs::Footstep::RIGHT) {
if (left_goal_state_->crossCheck(state)) {
return true;
}
}
}
return false;
}
double footstepHeuristicStraightRotation(
SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph)
{
FootstepState::Ptr state = node->getState();
FootstepState::Ptr goal = graph->getGoal(state->getLeg());
Eigen::Affine3f transform = state->getPose().inverse() * goal->getPose();
return (std::abs(transform.translation().norm() / graph->maxSuccessorDistance()) +
std::abs(Eigen::AngleAxisf(transform.rotation()).angle()) / graph->maxSuccessorRotation());
}
double footstepHeuristicStraight(
SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph)
{
FootstepState::Ptr state = node->getState();
FootstepState::Ptr goal = graph->getGoal(state->getLeg());
Eigen::Vector3f state_pos(state->getPose().translation());
Eigen::Vector3f goal_pos(goal->getPose().translation());
return (std::abs((state_pos - goal_pos).norm() / graph->maxSuccessorDistance()));
}
bool FootstepGraph::isGoal(StatePtr state)
{
FootstepState::Ptr goal = getGoal(state->getLeg());
if (publish_progress_) {
jsk_footstep_msgs::FootstepArray msg;
msg.header.frame_id = "odom";
msg.header.stamp = ros::Time::now();
msg.footsteps.push_back(*state->toROSMsg());
pub_progress_.publish(msg);
}
Eigen::Affine3f pose = state->getPose();
Eigen::Affine3f goal_pose = goal->getPose();
Eigen::Affine3f transformation = pose.inverse() * goal_pose;
return (pos_goal_thr_ > transformation.translation().norm()) &&
(rot_goal_thr_ > std::abs(Eigen::AngleAxisf(transformation.rotation()).angle()));
}
bool TransitionLimitXYZRPY::check(FootstepState::Ptr from,
FootstepState::Ptr to) const
{
// from * trans = to
const Eigen::Affine3f diff = to->getPose() * from->getPose().inverse();
const Eigen::Vector3f diff_pos(diff.translation());
if (std::abs(diff_pos[0]) < x_max_ &&
std::abs(diff_pos[1]) < y_max_ &&
std::abs(diff_pos[2]) < z_max_) {
float roll, pitch, yaw;
pcl::getEulerAngles(diff, roll, pitch, yaw);
return (std::abs(roll) < roll_max_ &&
std::abs(pitch) < pitch_max_ &&
std::abs(yaw) < yaw_max_);
}
else {
return false;
}
}
std::vector<FootstepState::Ptr>
FootstepGraph::localMoveFootstepState(FootstepState::Ptr in)
{
std::vector<FootstepState::Ptr> moved_states;
moved_states.reserve((2*parameters_.local_move_x_num + 1)*(2*parameters_.local_move_y_num + 1)*(2*parameters_.local_move_theta_num +1) - 1);
int x_num = parameters_.local_move_x_num;
int y_num = parameters_.local_move_y_num;
int theta_num = parameters_.local_move_theta_num;
if(x_num == 0) x_num = 1;
if(y_num == 0) y_num = 1;
if(theta_num == 0) theta_num = 1;
double move_x = parameters_.local_move_x;
double move_y = parameters_.local_move_y;
double move_t = parameters_.local_move_theta;
double offset_x = parameters_.local_move_x_offset;
double offset_y = (in->getLeg() == jsk_footstep_msgs::Footstep::LEFT) ?
parameters_.local_move_y_offset : - parameters_.local_move_y_offset;
double offset_t = parameters_.local_move_theta_offset;
bool have_offset = ((offset_x != 0.0) || (offset_y != 0.0) || (offset_t != 0.0));
for (int xi = - parameters_.local_move_x_num; xi <= parameters_.local_move_x_num; xi++) {
for (int yi = - parameters_.local_move_y_num; yi <= parameters_.local_move_y_num; yi++) {
for (int thetai = - parameters_.local_move_theta_num; thetai <= parameters_.local_move_theta_num; thetai++) {
if ( have_offset || (xi != 0) || (yi != 0) || (thetai != 0) ) {
Eigen::Affine3f trans(Eigen::Translation3f((move_x / x_num * xi) + offset_x,
(move_y / y_num * yi) + offset_y,
0)
* Eigen::AngleAxisf((move_t / theta_num * thetai) + offset_t,
Eigen::Vector3f::UnitZ()));
moved_states.push_back(
FootstepState::Ptr(new FootstepState(in->getLeg(),
in->getPose() * trans,
in->getDimensions(),
in->getResolution())));
}
}
}
}
return moved_states;
}
std::vector<FootstepState::Ptr>
FootstepGraph::localMoveFootstepState(FootstepState::Ptr in)
{
std::vector<FootstepState::Ptr> moved_states;
moved_states.reserve(local_move_x_num_ * local_move_y_num_ * local_move_theta_num_ * 8);
for (size_t xi = - local_move_x_num_; xi <= local_move_x_num_; xi++) {
for (size_t yi = - local_move_y_num_; yi <= local_move_y_num_; yi++) {
for (size_t thetai = - local_move_theta_num_; thetai <= local_move_theta_num_; thetai++) {
Eigen::Affine3f trans(Eigen::Translation3f(local_move_x_ / local_move_x_num_ * xi,
local_move_y_ / local_move_y_num_ * yi,
0)
* Eigen::AngleAxisf(local_move_theta_ / local_move_theta_num_ * thetai,
Eigen::Vector3f::UnitZ()));
moved_states.push_back(
FootstepState::Ptr(new FootstepState(in->getLeg(),
in->getPose() * trans,
in->getDimensions(),
in->getResolution())));
}
}
}
return moved_states;
}
FootstepState::Ptr FootstepGraph::projectFootstep(FootstepState::Ptr in,
unsigned int& error_state)
{
if(!use_pointcloud_model_) {
return in;
}
ros::WallTime start_time = ros::WallTime::now();
FootstepState::Ptr projected_footstep = in->projectToCloud(
*tree_model_,
pointcloud_model_,
grid_search_,
*tree_model_2d_,
pointcloud_model_2d_,
Eigen::Vector3f(0, 0, 1),
error_state, parameters_);
ros::WallTime end_time = ros::WallTime::now();
perception_duration_ = perception_duration_ + (end_time - start_time);
return projected_footstep;
}
FootstepState::Ptr FootstepGraph::projectFootstep(FootstepState::Ptr in,
unsigned int& error_state)
{
ros::WallTime start_time = ros::WallTime::now();
FootstepState::Ptr projected_footstep = in->projectToCloud(
*tree_model_,
pointcloud_model_,
grid_search_,
*tree_model_2d_,
pointcloud_model_2d_,
Eigen::Vector3f(0, 0, 1),
error_state,
plane_estimation_outlier_threshold_,
plane_estimation_max_iterations_,
plane_estimation_min_inliers_,
support_check_x_sampling_,
support_check_y_sampling_,
support_check_vertex_neighbor_threshold_);
ros::WallTime end_time = ros::WallTime::now();
perception_duration_ = perception_duration_ + (end_time - start_time);
return projected_footstep;
}
double footstepHeuristicStepCost(
SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph,
double first_rotation_weight,
double second_rotation_weight)
{
FootstepState::Ptr state = node->getState();
FootstepState::Ptr goal = graph->getGoal(state->getLeg());
Eigen::Vector3f goal_pos(goal->getPose().translation());
Eigen::Vector3f diff_pos(goal_pos - state->getPose().translation());
diff_pos[2] = 0.0; // Ignore z distance
Eigen::Quaternionf first_rot;
// Eigen::Affine3f::rotation is too slow because it calls SVD decomposition
first_rot.setFromTwoVectors(state->getPose().matrix().block<3, 3>(0, 0) * Eigen::Vector3f::UnitX(),
diff_pos.normalized());
Eigen::Quaternionf second_rot;
second_rot.setFromTwoVectors(diff_pos.normalized(),
goal->getPose().matrix().block<3, 3>(0, 0) * Eigen::Vector3f::UnitX());
// is it correct??
double first_theta = acos(first_rot.w()) * 2;
double second_theta = acos(second_rot.w()) * 2;
if (isnan(first_theta)) {
first_theta = 0;
}
if (isnan(second_theta)) {
second_theta = 0;
}
// acos := [0, M_PI]
if (first_theta > M_PI) {
first_theta = 2.0 * M_PI - first_theta;
}
if (second_theta > M_PI) {
second_theta = 2.0 * M_PI - second_theta;
}
//return (Eigen::Vector2f(diff_pos[0], diff_pos[1]).norm() / graph->maxSuccessorDistance()) + std::abs(diff_pos[2]) / 0.2 +
return (diff_pos.norm() / graph->maxSuccessorDistance()) + std::abs(diff_pos[2]) / 0.2 +
(first_theta * first_rotation_weight + second_theta * second_rotation_weight) / graph->maxSuccessorRotation();
}
double footstepHeuristicFollowPathLine(
SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph)
{
FootstepState::Ptr state = node->getState();
FootstepState::Ptr goal = graph->getGoal(state->getLeg());
Eigen::Vector3f goal_pos(goal->getPose().translation());
Eigen::Vector3f state_pos(state->getPose().translation());
Eigen::Vector3f state_mid_pos;
if (state->getLeg() == jsk_footstep_msgs::Footstep::LEFT) {
Eigen::Vector3f p(0, -0.1, 0);
state_mid_pos = state->getPose() * p;
} else { // Right
Eigen::Vector3f p(0, 0.1, 0);
state_mid_pos = state->getPose() * p;
}
double dist, to_goal, alp;
int idx;
Eigen::Vector3f foot;
dist = graph->heuristic_path_->distanceWithInfo(state_mid_pos, foot, to_goal, idx, alp);
//jsk_recognition_utils::FiniteLine::Ptr ln = graph->heuristic_path_->at(idx);
Eigen::Vector3f dir = graph->heuristic_path_->getDirection(idx);
Eigen::Quaternionf path_foot_rot;
path_foot_rot.setFromTwoVectors(state->getPose().matrix().block<3, 3>(0, 0) * Eigen::Vector3f::UnitX(),
dir);
double path_foot_theta = acos(path_foot_rot.w()) * 2;
if (path_foot_theta > M_PI) {
path_foot_theta = 2.0 * M_PI - path_foot_theta;
// foot_theta : [0, M_PI]
}
double step_cost = to_goal / graph->maxSuccessorDistance();
double follow_cost = dist / 0.02; // ???
double path_foot_rot_cost = path_foot_theta / graph->maxSuccessorRotation();
Eigen::Vector3f goal_diff = goal_pos - state_pos;
Eigen::Quaternionf goal_foot_rot;
goal_foot_rot.setFromTwoVectors(state->getPose().matrix().block<3, 3>(0, 0) * Eigen::Vector3f::UnitX(),
goal->getPose().matrix().block<3, 3>(0, 0) * Eigen::Vector3f::UnitX());
double goal_foot_theta = acos(goal_foot_rot.w()) * 2;
if (goal_foot_theta > M_PI) {
goal_foot_theta = 2.0 * M_PI - goal_foot_theta;
}
double goal_foot_rot_cost = goal_foot_theta / graph->maxSuccessorRotation();
//return step_cost + follow_cost + (4.0 * goal_foot_rot_cost) + (0.5 * path_foot_rot_cost);
return 2*(step_cost + follow_cost + (0.5 * path_foot_rot_cost));
}
